Optical coherence tomography as a rapid, accurate, non-contact method of visualizing the palisades of vogt

ABSTRACT

The innovation provides for a system and method available to image and visualize the palisades of Vogt via a non-contact process, analyze the image volumes acquired, evaluate the status of the palisades of Vogt from the data represented therein, and display the data in real-time or as a part of a medical record for ongoing consideration and evaluation.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Patentapplication Ser. No. 61/448,389 entitled “OPTICAL COHERENCE TOMOGRAPHYAS A RAPID, ACCURATE, NON-CONTACT METHOD OF VISUALIZING THE PALISADES OFVOGT” filed on Mar. 2, 2011. The entirety of the above-noted applicationis incorporated by reference herein.

NOTICE ON GOVERNMENT FUNDING

This invention was made with government support under EY08098 andEY03263 awarded by the National Institutes of Health (NIH). Thegovernment has certain rights in the invention.

ORIGIN

The innovation disclosed herein relates to stem cells and morespecifically, a system and method to image the palisades of Vogt usingOptical Coherence Tomography (OCT).

BACKGROUND

Stem cell deficiency is seen in many ocular diseases and can lead toblindness. The condition is associated with a wide variety of maladiesincluding burns, contact lens wear, dry eye, topical medications, andocular disease associated with immunologic disorders and can even beseen postoperatively. Treatment of stem cell depletion associated withthese conditions has been complicated by the inability to assess thestem cell niche in-vivo. For example, ten million people are bilaterallyblinded by conditions with corneal involvement and an additional twomillion cases of monocular corneal blindness arise each year fromtrauma. Stem cell therapy and transplantation offers the possibility ofcure for many of them.

An instance of one of the stem cell niches is the Palisades of Vogt, apoorly understood structure in the corneal limbus that provides themicroenvironment necessary for survival and function of the cornealepithelial stem cells. Considerable variability in the size, shape andspecific location of the palisades complicates identification andharvesting of stem cells for transplantation. Indeed, there are changesin the palisades in the normal course of aging as well as during diseaseconditions. While in-vivo confocal microscopy can be used to identifythe palisades, it requires direct contact with the eye, is timeconsuming and covers a very limited area with each scan.

SUMMARY

The following presents a simplified summary of the innovation in orderto provide a basic understanding of some aspects of the innovation. Thissummary is not an extensive overview of the innovation. It is notintended to identify key/critical elements of the innovation or todelineate the scope of the innovation. Its sole purpose is to presentsome concepts of the innovation in a simplified form as a prelude to themore detailed description that is presented later.

In accordance with an aspect of the innovation, a method of visualizingthe palisades of Vogt is provided. The method includes imaging thepalisades of Vogt via a non-contact in-vivo process; and evaluating thepalisades of Vogt image on a display screen or displaying the image inreal time to visualize the palisades of Vogt image during medicalprocedures.

In accordance with another aspect of the innovation, imaging thepalisades of Vogt via a non-contact in-vivo process is made possible byOptical Coherence Tomography.

In accordance with another aspect of the innovation, a system forimaging palisades of Vogt is provided and includes an imaging componentto take non-contact images of the palisades of Vogt, an analysiscomponent to analyze the images, and data storage to store the images incategories for further evaluation, wherein the images are processed tofacilitate visualization of the palisades and reconstructed in C-modeslicing or with 3D modeling.

To the accomplishment of the foregoing and related ends, certainillustrative aspects of the innovation are described herein inconnection with the following description and the annexed drawings.These aspects are indicative, however, of but a few of the various waysin which the principles of the innovation can be employed and thesubject innovation is intended to include all such aspects and theirequivalents. Other advantages and novel features of the innovation willbecome apparent from the following detailed description of theinnovation when considered in conjunction with the drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram illustration of an imaging/analysis system forin-vivo imaging of palisades of Vogt in accordance with aspects of theinnovation.

FIG. 2 is a block diagram illustration of an analysis component of thesystem of FIG. 1 in accordance with aspects of the innovation.

FIG. 3 is a block diagram showing a methodology of imaging and analyzingpalisades via Optical Coherence Tomography in accordance with aspects ofthe innovation.

FIGS. 4A-4C are images of an eye and the palisades of Vogt in accordancewith aspects of the innovation.

FIGS. 5A-5H are images comparing an ocular surface in a surviving andfailed keratolimbal allograft in accordance with aspects of theinnovation.

FIG. 6A is a three-dimensional reconstruction of a limbal area showingthe palisades of Vogt in accordance with aspects of the innovation.

FIG. 6B is one of the planes of the OCT image stack that was used togenerate the reconstruction shown in FIG. 6A in accordance with aspectsof the innovation.

FIGS. 7A-7C are three-dimensional reconstructions of radial ridgesextending from a corneal margin in accordance with aspects of theinnovation.

FIG. 7D is one plane of the OCT image stack that was used to generatethe reconstructions shown in FIGS. 7A-7C in accordance with aspects ofthe innovation.

FIGS. 8A-8C are OCT images that are marked (white line) to display theregion that will be reconstructed in C-mode images, whereby C-modeimaging allows sectioning along any plane in accordance with aspects ofthe innovation.

FIGS. 9A-9B are images of serial confocal stacks labeled with collagenVII stitched and reconstructed in 3D in accordance with aspects of theinnovation.

FIGS. 10A-10E are images of 3D confocal reconstructions of differentareas of the limbus in accordance with aspects of the innovation.

FIGS. 11A-11B are images correlating un-mounted Optical CoherenceTomography and confocal images in accordance with aspects of theinnovation.

FIGS. 12A-12F are images correlating mounted Optical CoherenceTomography and confocal images in accordance with aspects of theinnovation.

FIGS. 13A-13C are images with Optical Coherence Tomography with C-modereconstruction in accordance with aspects of the innovation.

FIG. 14A is an image of a 3D reconstruction of an Optical CoherenceTomography volume segmented to isolate the palisades of Vogt inaccordance with aspects of the innovation.

FIG. 14B is a 3D confocal volume reconstruction of the same areadisplayed in FIG. 14A in accordance with aspects of the innovation.

FIG. 14C is a maximum intensity projection of the same stack set used toreconstruct FIG. 14B in accordance with aspects of the innovation.

FIGS. 15A-15C are enface views of the corneo-limbal surface acquiredwith OCT.

FIGS. 15D-15F are examples of C-mode reconstructions of palisades ofVogt patterns derived from the same image volumes displayed in FIGS.15A-15C in accordance with aspects of the innovation.

FIGS. 16A-16C are enface views of the corneo-limbal surface acquiredwith OCT in accordance with aspects of the innovation.

FIGS. 16D-16F are examples of C-mode reconstructions of possible areasof clipped palisades of Vogt derived from the same image volumesdisplayed in FIGS. 16A-16C in accordance with aspects of the innovation.

DETAILED DESCRIPTION

The innovation is now described with reference to the drawings, whereinlike reference numerals are used to refer to like elements throughout.In the following description, for purposes of explanation, numerousspecific details are set forth in order to provide a thoroughunderstanding of the subject innovation. It may be evident, however,that the innovation can be practiced without these specific details. Inother instances, well-known structures and devices are shown in blockdiagram form in order to facilitate describing the innovation.

While specific characteristics are described herein (e.g., thickness),it is to be understood that the features, functions and benefits of theinnovation can employ characteristics that vary from those describedherein. These alternatives are to be included within the scope of theinnovation and claims appended hereto.

While, for purposes of simplicity of explanation, the one or moremethodologies shown herein, e.g., in the form of a flow chart, are shownand described as a series of acts, it is to be understood andappreciated that the subject innovation is not limited by the order ofacts, as some acts may, in accordance with the innovation, occur in adifferent order and/or concurrently with other acts from that shown anddescribed herein. For example, those skilled in the art will understandand appreciate that a methodology could alternatively be represented asa series of interrelated states or events, such as in a state diagram.Moreover, not all illustrated acts may be required to implement amethodology in accordance with the innovation.

Referring now to the figures, FIG. 1 is a block diagram illustration ofan example system 100 for imaging and analyzing palisades of Vogt(hereinafter “palisades”) via Optical Coherence Tomography (hereinafter“OCT”). OCT provides a first opportunity for rapid, non-contact,three-dimensional in-vivo imaging of the palisades. Development of thistechnique will provide a vehicle to accurately harvest or deliver stemcells for transplantation, to monitor the palisades clinically forbetter diagnosis, follow-up and staging, and to identify patients atrisk for stem cell deficit early in the disease process. The techniquewill also provide an additional vehicle for the study of the palisadesand for research into ocular diseases. The system 100 includes animaging component 102 (e.g., OCT component) that provides an image ofthe palisades, an analysis component 104 to analyze the OCT image, anddata storage component 106 to store results from the analysis component104.

As will be described further below, the OCT component 102 takes imagesof the palisades for further evaluation. The OCT images of the palisadesare transferred to the analysis component 104 for further processing.For example, the analysis component 104 may identify, classify, monitor,etc. palisades in the images as will be described below with referenceto FIG. 2. The analysis component 104 communicates with the data storagecomponent 106 to exchange the palisades images or information relatingto the palisades images.

The data storage component 106 stores the images for further retrievaland evaluation. For example, the data storage component 106 may storethe images in categories or classifications, such as but not limited to,healthy, unhealthy, demographics (e.g., gender, age, race, etc.), etc.Further, the data storage component 106 may break down each categoryinto sub-categories. For example, the unhealthy category may includespecific health related sub-categories.

Referring to FIG. 2, the analysis component 104 includes anidentification component 202 to identify suitable images, aclassification component 204 to classify and categorize the images, anda monitoring component 206 to monitor changes in the image as comparedwith other sets to determine the status of the palisades. Theidentification component 202 identifies each palisades image transferredfrom the OCT component 102 to determine a status of the image. Forexample, the identification component 202 can determine if the palisadesimage reflects healthy or unhealthy or if the image indicates that thetissue would be suitable for donation, etc. In order to do so, theidentification component 202 can reference information (e.g., images)from a volume of images to make appropriate comparisons and properidentifications.

The classification component 204 can classify each palisades image incategories that correspond to those of the data storage component 106prior to transferring the image to the data storage component 106. It isto be appreciated that the images need not be classified prior tostorage in the data storage component 106. The data storage component106 can simply store the image in a non-classified category to awaitfurther processing and/or classification. Once the images areclassified, they are transferred to the data storage component 106 forstorage until needed. The classification component 204 can classifyautomatically or manually. In regards to automatic classification, theclassification component 204 can learn how to automatically classifyimages based on images already stored in the data storage component 106.In other words, the classification component 204 can compare a new imageto images stored in the data storage component 106 to determine whichcategory the images belong.

Manual classification can be performed by any qualified person (e.g.,doctor, medical technician, etc.) who can identify normal and abnormalcharacteristics of the palisades. For example, during manualclassification, the qualified person can further identify certainabnormalities that cannot be detected automatically. These images can beclassified in specialized categories that may warrant additionalresearch.

The monitoring component 206 can monitor the trend (e.g., health)described by the images. For example, multiple images of a particularpatient can be taken over a given time period. As each image is takenand transferred to the analysis component 104, the monitoring component206 can compare the new image with one or more previous images from thepatient to determine a trend. For example, does the trend indicate thatthe patient is improving, staying the same or getting worse. Further,the monitoring component 206 can be used for onscreen evaluation or canbe used to project images on a display screen or on the surface of theeye in real-time during surgical/medical procedures.

Referring to FIG. 3, a method of imaging and analyzing via OCT will nowbe described. At 302, an image of the palisades of Vogt is taken via theOCT component 102 by the method described below. At 304, the image istransferred to the analysis component 104. At 306, the identificationcomponent 202 identifies the elements within the image by referencinginformation (e.g., images) from a volume of images to make appropriatecomparisons and proper identifications. At 308, the classificationcomponent 204 classifies, automatically or manually, the image into acategory corresponding to categories in the data storage component 106.At 310 the monitoring component 206 evaluates the image against storedimages to determine a trend, as described above. At 312, the image istransferred to the data storage component 106 and stored in a categoryas described above for further processing and/or evaluation.

As mentioned above, development of OCT will provide the means toaccurately harvest stem cells for transplantation, to monitor thepalisades clinically for better diagnosis, follow-up and staging, and toidentify patients at risk for stem cell deficit early in the diseaseprocess. Stem cells require a highly specialized environment which canprovide protection and nutrition for the cells and access to the tissuethat they support. FIGS. 4A-4C are images 400 of an eye showing a regionbetween the cornea and the sclera, known as the limbus, that providesthis specialized environment, known as the palisades of Vogt. Stem cellsin the limbus produce cells which migrate to the epithelial surface andthe move toward the center of the cornea. The corneal epithelium is in aconstant state of renewal with complete turnover of the cell populationevery five to seven days. This dynamic, rapid renewal is necessary tomaintain the transparent, avascular, highly organized tissue of thecornea.

The palisades are regarded as the putative limbal epithelial stem cellniche. Although, first noted in 1866 and described in detail in 1921,the palisades remain a poorly understood and elusive region. Becausetheir function was not clear, there was no strong motivation to clearlydescribe the palisades. Rapid progress in stem cell research, however,has directed more attention toward the palisades as numerousinvestigations point to the palisades as the location of corneal stemcells that maintain corneal epithelial homeostasis and clarity. Ideallythe corneal stem cells would be visualized directly, but in the absenceof such technology, the palisades can be used to determine the generallocation and status of the stem cells. The difficulty in defining thepalisades arises from their unique structure, configuration anddimension in each individual and from the fact that they are difficultto visualize. Deeper understanding of the palisades is crucial todeveloping new stem cell therapies targeted at restoring vision andmaintaining the health of the eye, for without the environment providedby the limbal palisades there are no limbal stem cells to sustain thecornea. The convergence of progress in the development of OCT, advancesin 3-dimensional stitching and rendering techniques and improvements inimmunofluorescent staining and microscopy now offer the opportunity toreexamine the structure of the palisades in general and to visualize thefull structure of the palisades in-vivo for the first time.

Still referring to FIGS. 4A-4C, the palisades, which have a structure asunique as fingerprints, reside in a 1-2 mm band of the connective tissueprimarily in the superior and inferior regions of the corneosclerallimbus and follow an irregular and undulating radial pattern around thecornea. The conjunctival epithelium becomes thickened in this area andforms radial zones called interpalisades or epithelial rete ridges.Thus, the epithelium comes into direct contact with the palisade region.Terminal capillaries from the anterior ciliary arteries make this regiona rich, stable environment for stem cells. The size, shape andconfiguration of the palisades changes over time in response to acquiredor congenital conditions, aging, surgery and medication. Destruction ofthe palisades and the associated destruction of the stem cells theycontain results in conjunctivalization of the cornea, vascular invasionand concomitant blindness. Restoration of the palisades and theirresident stem cells results in clearing of the cornea and restoration ofvision.

Visualization of portions of the palisades is sometimes possible using aslit lamp and can be enhanced by fluorescein imaging. However, in up to20% of patients palisades cannot be identified clinically using currentmethods and none of these techniques give an overall view of thedimension and structure of the whole palisade region. Confocalmicroscopy has been used to visualize and characterize changes in thepalisades associated with age and to retrieve targeted biopsies whichproduce higher yields of stem cells. Confocal microscopy has also beenproposed as a technique to monitor the status of keratolimbal allograftsfollowing transplantation. The technique, however, is limited by highmagnification which restricts the area of the scan. In addition, in-vivoconfocal microscopy requires direct contact with the eye and anesthesia,either of which may inadvertently cause more damage to an eye that hasalready suffered insult. Further, relatively long periods of time arerequired for scans of small portions of the eye and the quality of thescans may be compromised by blinking, anxiety and involuntary motion.

For example, FIGS. 5A-5H compare images 500 an ocular surface in asurviving (FIGS. 5A-5D) and failed (FIGS. 5E-5H) keratolimbal allograft.FIG. 5A shows a slit-lamp photo of a transparent cornea with a fewvessels at the limbus. In FIG. 5B, the palisades, denoted by the bluearrow, extend into the limbal epithelium in a regular arrangement, withslender vessels inside. Further, only a few dendritic cells weredetected and are denoted by the red arrow. Finally, FIG. 5B illustratesthat the morphology of the limbalepithelial cells was normal. FIGS. 5Cand 5D illustrate central corneal cells displaying a polygonal shape anda regular arrangement, and that the morphology of the central stromalcells was normal respectively.

FIG. 5E shows a slit-lamp photo of a failed graft showing an opacifiedcornea with neovascularization. FIG. 5F shows that the palisades weredestroyed and that the stromal process was thin and irregular. Further,a large number of dendritic cells, denoted by the blue arrow, weredetected. FIG. 5E also shows that the epithelial cells between stromalprocess had relatively large cell bodies, denoted by the red arrow.FIGS. 5G and 5H show that the central corneal epithelial cells werelarger and that the central corneal stroma was hyperreflectiverespectively.

Loss of the palisades may be partial or complete and may be caused byacquired or congenital conditions and may present as the primary orsecondary issue. Limbal epithelial stem cell deficiency (LSCD) refers tothe spectrum of conditions which cause loss of stem cells and thepalisades. Patients with LSCD may experience significant pain, severevision loss and photophobia. Included in causes of LSCD are:keratolimbal allograft transplantation, acid and alkali burns, thermalburns, Stevens-Johnson syndrome, ocular cicatrizing pemphigoid, multiplesurgeries, contact lens wear, microbial infections, ocular surfacedisease, topical medications, ultraviolet and ionizing radiation,aniridia, congenital erthrokeratodermia, keratitis associated withendocrine deficiencies, neurotrophic keratopathy, chronic limbitis,peripheral ulcerative disorders, pterygium, chronic bullous keratopathy,severe dry eye, Peters anomaly, ecdodermal dysplasia, long-term use oftopical medications including antibiotics, corticosteroids, B-blockers,pilocarpine, mitomycin-C. Other diagnoses that may contribute to stemcell failure include keratoconjunctivitis sicca, rosacea, and HSVkeratitis.

Prior to 1989 treatment for total LCSD was limited to penetratingkeratoplasty, tarsorrhaphy and the use of artificial tears, none ofwhich address the cause of the disease. With the advent of keratolimbalallograft transplantation it has become possible to not only treat thecause of LCSD but in some instances, to cure the disease. Continuedprogress in the field has produced methods of cultivating and expandingstem cells ex-vivo to reduce the size of the tissue that must beharvested. This is particularly important in the case of autograftsbecause harvesting a large an area of the limbus from the donor eye mayproduce LCSD in that eye, thus compromising the good eye in an effort torescue the afflicted eye. Autografts remain the most desirabletransplant because they do not require the patient to maintainimmunosuppressive therapy following surgery. In instances where the LCSDis not total there are more treatment options.

Allografts from living relatives or cadavers may also be used, althoughthe success rate is not as high. In some instances of allograft fromclose relatives the match may be good enough that immunosuppression isnot required. Graft rejection remains a major concern for patients withsevere disease. Development of enhanced transplant techniques continuesand includes design of new synthetic scaffolds to maintain and supportthe cells during transplantation or use of amniotic membrane as asubstrate. Each of these techniques has advantages and drawbacks, butall of them would benefit from an accurate, non-contact way to monitorpre and post-surgical progress.

Progress in understanding the nature of stem cell niches has beenhampered by the fact that it has not been possible to observe andmonitor adult stem cell niches in-vivo. Previous 3D reconstructions ofthe palisades have been conducted ex-vivo with confocal imaging. Inthese studies, the corneal epithelium is used as a locator for the roofof the palisade structure, but the structure itself is not clearlydefined.

OCT was invented in 1991 and was initially used to image the retina. In2001 the first anterior segment OCT was used to investigate anteriorchamber and cornea. Recent advances in OCT technology allow acquisitionof scans at ultrahigh speeds up to 400,000 axial scans per second. Thisnon-contact technique allows internal structures to be imaged inbiological tissues in-vivo by measuring the delay caused by reflectionof light from the sample. High-resolution images with exquisite detailare acquired rapidly and at a comfortable working distance from thepatient by using long-wavelength laser light. Recognition of tissueboundaries depends on contrast between backscattered or reflected signalstrength.

OCT has never been described as a method to visualize the pattern of thepalisades until a recent pilot study in which a Cirrus high definition(HD)-OCT system and a modified Bioptigen spectral-domain opticalcoherence tomography system were used to acquire images of the corneallimbus. The purpose of this pilot study was to demonstrate in-vivovisualization of the palisades in living human eyes using spectraldomain (SD)-OCT. The Bioptigen system had 3.0- to 3.5-μm axial imageresolution and an imaging speed of 28.000 axial scans per second, andthe Cirrus OCT had 5-μm resolution and a speed of 27,000 axial scans persecond. 3D image sets were analyzed using C-mode slicing to reconstructthe area of the epithelial basement membrane. Reconstruction of thecorneal limbal region via 3D OCT image sets revealed the configurationof the palisades.

Further, the pilot study OCT images clearly showed the epithelium andthe epithelial rete ridges extending downward interdigitated by a densestructure. This is completely consistent with the configuration andlocation of the palisades. Preliminary reconstructions of this area inthree-dimensional models reveal a structure with features thatcorrespond to documented images of the palisades including areas thatradiate outward from the corneal margin with connections betweenstructures and descending crypt-like structures. These three-dimensionalmodels provide a complex, detailed representation of this uniquestructure and, not surprisingly, reveal it to be more intricate thanpreviously described. The rapid acquisition of images with OCT allowsacquisition of 3D volumes that encompass the entire limbus. Developmentof analysis tools and software that allow reconstruction of thepalisades from the full circumference of the cornea will for the firsttime allow rapid, non-contact, accurate visualization of the palisadesof each individual patient.

For example, referring to FIGS. 6A and 6B, FIG. 6A is an image 600A of arotated model of the same limbal area image 600B in FIG. 6B. Thepalisades are shown in magenta and the lower margin of the cornea inblue. Further, referring to FIGS. 7A-7D, images 700 of radial ridgesextending from the corneal margin are shown in FIG. 7A. FIG. 7B shows aportion of the same sample pictured from the side. Crypt-like structuresextending below a dense mesh can be seen. FIGS. 7C and 7D are the samedataset, whereby FIG. 7C shows the 3D reconstruction of the palisaderegion and FIG. 7D shows one slice of the original OCT image.

Thus, OCT offers an alternative imaging modality that eliminates all thelimitations described above relating to confocal microscopy and otherconventional methods. In other words, the innovation disclosed hereinestablishes that OCT is capable of high-resolution non-contact imagingof the palisades and has distinct advantages over confocal imaging, aswill be subsequently described.

Twenty human donor corneal rims were recovered in organ culture chamberscontaining Optisol GS media as provided by the tissue bank followingcorneal transplant surgeries. The donor tissues were 24-70 years old andwere fixed 2-7 days post-mortem. Epithelium had been removed around thecorneal button during the surgery, but was present in the limbal regionand conjunctiva.

The rims were imaged with a high-speed ultra-high-resolution OCT scannerusing a raster pattern. Scans sampled a 2×2×2 mm region of tissue with512×180×1024 measurements. The scanner included a 100 nm bandwidth lightsource centered at 870 nm yielding a coherence length of 2 μm in tissue.Images were reconstructed and processed using spectral OCT (SOCT)browser software developed by others.

Immunolabeling was performed by washing the corneal rims with phosphatebuffered saline (PBS) for approximately 15 minutes two times prior tofixation in 4% paraformaldehyde (PFA) for a predetermined time period(e.g., 24 hours) at 4° C. The tissue was washed in PBS-Tx (PBScontaining 0.3% triton x-100) for approximately 15 minutes three timesand then permeabilized with 0.5% triton x-100 for approximately twohours at room temperature. Following permeabilization, the tissue waswashed with PBS-Tx for approximately 5 minutes three times. Blocking wasdone by using 10% heat inactivated goat serum (containing 0.3% tritonx-100) for approximately 2 hours at room temperature. Tissue was thenwashed with PBS-Tx for approximately 10 minutes at room temperature andincubated with culture supernatants containing primary mouse monoclonalanti-human Type VII collagen antibody 5D2 diluted 1:1 with the blockingbuffer at room temperature for approximately 1 hour followed byincubation at 4° C. for a predetermined timer period (e.g., 12 hours).The tissue was then washed with PBS-Tx for approximately 20 minutes 5times. Alexafluor 488 conjugated goat anti-mouse IgG was used for thesecondary antibody and was incubated for two hours at room temperaturewithout light. DAPI or 4′,6-diamidino-2-phenylindole (50 ul, 300 nM) wasadded directly on the secondary antibody for approximately 20 minutes.Finally the tissue was washed with PBS-Tx for approximately 20 minutesthree times and was mounted. Large-format spacers for whole mountinghuman corneal rims were made from shelf liner. One-inch circles werepunched with a lever punch and the spacer was fixed to a large formatslide with an adhesive. Corneal rims were cut in half and relief cutswere made in the sclera and cornea to allow the rim to lie flat. Thecorneal rims were placed in the well created by the spacer andImmu-mount was used to fill the well. Large format coverslips were usedto seal the mounted specimens. Whole mounting the tissue with spacersoffers the distinct advantage of maintaining the morphology of thetissue, which is critical for accurate three-dimensional (3D)reconstruction.

Confocal microscopy was conducted on an Olympus FV1000 inverted laserscanning confocal microscope system with a 20× oil (refractive index0.85) objective. Image stack acquisition was under sampled in the XYplane and optimized for the Z dimension to allow the best possiblereconstructions and to control file sizes and acquisition time. Thedepth of the stacks ranged from 50-150 microns. Images were saved in thenative Olympus Image Binary (OIB) format and subsequently converted to 8bit RGB (red, green, blue).

Reference image sets of corneal rims whole mounted andimmunofluorescently labeled to define the basement membrane of thelimbus were acquired with laser scanning confocal microscopy. Large (upto 50) sequential confocal stack sets were stitched together and 3Dmodels were built. This kind of acquisition and reconstruction is notpossible in living subjects because of the need for a fluorescent labeland the time required for acquisition. 3D display of reconstructedstacks is available as supplementary material. OCT image sets werereconstructed in the SOCT Browser, smoothed with a rolling average andthen viewed in a selective en-face mode using C-mode slicing. Theconfocal and OCT image sets were correlated to identify the samepalisade structures.

OCT image sets were acquired before or after tissue fixation with nosignificant difference in image quality. Initial reconstruction andprocessing in SOCT Browser software included a rolling average to smooththe image. Enface imaging was sometimes able to hint at the underlyingstructure, but was inadequate for a full understanding of the region.Detailed visualization of the palisade region was conducted with C-modesectioning which allows data to be sectioned virtually along arbitraryplanes and in varying thicknesses relative to the direction of scanacquisition. This allows structures embedded within a volume to beexposed and improves the visualization of pathologic features, as shownin FIGS. 8A-8C. Specifically, FIGS. 8A-8C illustrate images 800 viaC-mode imaging, which allows sectioning along any plane to view atissue, whereby the depth can be adjusted to accommodate the depth ofthe tissue. FIG. 8A illustrates an enface image with horizontal andvertical axes of orthogonal sections marked. FIG. 8B illustrates ahorizontal orthogonal view showing the planes that are included in theenface image in white. FIG. 8C illustrates a vertical view showing theplanes that are included in the enface view in white.

The method of mounting the tissue for laser scanning confocal microscopyallowed the acquisition of many contiguous stacks of large areas oftissue without distorting the morphology. These stacks were stitchedtogether to view a large area of the limbus and the reconstructionsreveal detailed 3D structure of the palisades that has not previouslybeen well represented, as shown in the images 900 in FIGS. 9A-9B.Specifically, FIG. 9A illustrates the maximum intensity projectionthrough z plane reveals overall limbal structure, where the scale barequals 635 um. FIG. 9B illustrates the same stack reconstructed in 3Dand rotated to show the orientation of structures relative to eachother.

In addition to presenting the variability of the palisade structuresthese images reveal the dimension and variability of the limbalstructure and the transition of the limbus to the cornea andconjunctiva. When the confocal stacks are reconstructed in 3D orrendered with maximum intensity projections through the stack theyreveal a complex and varied structure that demonstrates a wide range ofdifferent configurations even within the same subject, as shown in theimages 1000 in FIGS. 10A-10E. Specifically, FIGS. 10A-10C illustrate 3Dconfocal reconstructions of different areas of the limbus from the samesubject. FIG. 10D illustrates a 3D reconstruction of a limbal regionshowing an extensive finger-like pattern. FIG. 10E illustrates a 3Dreconstruction of a limbal region showing an undulating and irregularpalisade pattern.

All of the observed structures rise from the basement membrane into theepithelium when viewed in 3D. Often ridge-like areas taper off tofinger-like projections in lateral and central areas, giving theimpression that the finger-like regions are the beginning or end of theridges. These structures have been described as focal stromalprojections. In some areas the ridges are mesh-like while in others theyare very clear and rhythmic with some showing many finger-likestructures. In some samples, there are very few palisade ridges or justa few of the finger-like structures.

FIGS. 11A-11B and 12A-12F show images 1100, 1200 respectively of OCT andconfocal image stacks were then compared to identify the same regions ineach imaging method. The correlation between the methods is clearwhether OCT is acquired in unfixed or fixed and mounted tissue.Specifically, FIG. 11A illustrates an un-mounted tissue reconstructed inC-mode imaging showing a mesh-like palisade pattern. FIG. 11Billustrates the same region reconstructed with confocal stacks stitchedtogether. As illustrated in these images, there is a slight change inthe angle between the two images because the region was flatter forconfocal imaging. The black arrows identify an easily recognizablestructure but the whole meshwork can be identified in each image.

FIGS. 12A and 12B illustrate an enface view of tissue and an orthogonalview of tissue at the level of the red line respectively. FIG. 12Cillustrates an enface C-mode image reconstructed through the palisaderegion. FIG. 12D illustrates an orthogonal view of C showing the planesincluded in the reconstruction. FIG. 12E illustrates a maximum intensityprojection of a series of 48 confocal image stacks stitched together toshow the same region of the limbus. FIG. 12F illustrates an overlay ofOCT enface C-mode image (red) and the confocal maximum intensitystitched image (green). Coincident areas are displayed in yellow. Asillustrated in these images there is no distortion between these imagesets because they were both acquired from the same mounted tissue.

Reconstruction in 3D reinforces the correlation between the two methodsand clearly demonstrates the ability of OCT to reveal detailed andintricate structures in the limbus, as shown in the images 1300 in FIGS.13A-13C. Specifically, FIGS. 13A and 13B illustrate an enface image oflimbal rim and an orthogonal view showing palisade structuresrespectively. FIG. 13C illustrates a C-mode reconstruction of palisaderegion showing a very regular palisade pattern in the anterior limbuswith an extensive meshwork pattern in the posterior limbus.

These same image sets can be reconstructed in to 3D volumetric modelswhich provide more information about the depth of the palisades andtheir relationship to each other, as shown in the images 1400 in FIGS.14A-14C. Specifically, FIG. 14A is a 3D Reconstruction of OCT image setshowing palisade pattern. FIG. 14B is a 3D reconstruction of confocalmicroscopy stack set showing the same region. FIG. 14C illustrates amaximum intensity projection of the area shown in B.

Volumetric data sets provide more information about the limbus than haspreviously been available. The overall pattern of the palisades can beviewed, as shown in in the images 1500 in FIGS. 15A-15F, and the zoomlevel increased to provide a more restricted field with greater detail.Specifically, FIGS. 15A-15C are enface views of the surface of thetissue. FIGS. 15D-15E are C-mode views of the corresponding palisaderegions showing a wide variety of palisade patterns. Reviewing of volumedata sets can also provide information about how tissue is being handledand the integrity of different tissue layers.

In some instances reconstruction revealed palisade areas that extendedall the way to the cut edge of the cornea, as shown in the images 1600in FIGS. 16A-16F. Specifically, FIGS. 16A and 16D are enface viewsshowing the cut edge, which is not perpendicular to the surface of thecornea. From this angle it does not appear that there has been anyclipping. FIGS. 16B and 16E are C-mode reconstructions at the level ofthe palisades showing palisade structures coming right up to and endingabruptly at the cut edge. FIGS. 16C and 16F are vertical orthogonalviews of the same section showing the cut edge of the cornea. The planesof the c-mode display are marked in black and the area of the cut edgeis highlighted with a black arrow. These cuts are stepped in two stages.

Direct visualization of the corneal epithelial stem cells in vitro isnot currently possible, but since the palisades provide the environmentnecessary for the survival of these cells they can be used as a generalindicator of the overall health of the limbus and presence of stemcells. Others have reported three distinct palisade patterns; a standardpattern, an exaggerated pattern, and an attenuated pattern. The patternsdisclosed herein fall generally into these three categories, but it islikely that further characterization of the palisade structures mayproduce finer distinctions in both types and overall dimension of thestructures. This study and others clearly illustrate the need to developa deeper understanding of the architecture of the palisades and definethe relationship of that structure to a functional stem cell population.Here, the rapid acquisition of images with OCT allowed acquisition of 3Dvolumes that encompass large areas of the limbus, providing image setsthat can be acquired from living patients and are not available withother imaging technologies. Other imaging methods have distinctlimitations when working with a structure as dynamic as the limbus; theycannot describe the overall structure of the palisades and cannoteffectively evaluate changes in the palisades over time. Observation andclassification of overall palisade patterns requires these macroscopicviews and the convenience and speed of OCT imaging makes clinicalrecording and tracking of palisade structures possible for the firsttime.

Image sets acquired with OCT and reconstructed with C-mode imaging inthe present study provided a complex, detailed representation of thisunique structure and revealed it to be more intricate than previouslydescribed. Likewise, 3D reconstructions from laser scanning confocalimaging also provided a detailed and complex portrait of this perplexingregion and underscored the necessity of 3D visualization of thepalisades and the need for further understanding of the structure,function and interactions therein. Areas with distinct, clear structurescould be matched between the two imaging modalities to demonstrate thatOCT does image the palisades. However, the posterior palisade area wassometimes very convoluted and in some instances extended deeper thanconfocal microscopy could penetrate. In these areas OCT was able toprovide a more accurate representation of the palisade structure, asshown in FIGS. 13A-13C and 15A-15F, and the folding is very complex.Orthogonal images could be found but it is not yet clear whether truecrypts are depicted or whether these shapes are created by the intricatefolds.

The non-contact nature and speed of OCT imaging could greatly facilitatefuture studies of the palisades. These investigations can reveal detailsof the anatomical status and changes in the limbus and allow correlationbetween those changes with different disease processes, withpost-surgical remodeling and restoration of the palisades and in normalaging. Investigation into the palisade structure present in children andyoung adults could facilitate the understanding of developmental changesin the palisades. OCT imaging has the potential to enable researchers tointerpret the significance of the palisade structure in relation todifferent conditions and determine the impact of variations in the sizeand pattern of palisades on corneal physiology. In the clinic,visualization of the full dimension of the palisades of individualpatients could allow temporal tracking of changes in the palisades.Evaluation of the entire corneal stem cell niche of a donor eye prior toharvesting for autograft would allow better harvesting and enhancetargeted biopsies and help to ensure the health of the donor eye. Forpatients with full LSCD this might allow the success of their limbaltransplant to be assessed prior to corneal transplant. Following cornealsurgery, OCT evaluation of the palisades could provide a window ofopportunity to preemptively diagnose and intervene to treat transplantsin danger of failure. Further investigation into the distinctionsbetween different palisade configurations could reveal remodelingpatterns in the palisades that are indicative of different conditionsand this could potentially become an early diagnostic tool. The imageprocessing used in this study to view selective en-face fields of thelimbus was all conducted post-processing and while this is acceptablefor research, development of analysis tools and software that allowreal-time selective en-face reconstruction of this specific region willmake OCT an even more valuable clinical and surgical tool.

During imaging studies many of the limbal rims that were availablepost-transplantation were not useful for full reconstruction anddescription of the 3D morphology because the anterior palisade regionhad been clipped during harvesting of the corneal button. This couldsimply be due to handling during punching of the button and processingprior to surgery, or the button may have been rejected for transplantafter being punched. However, it is possible that the unintentionaltransplantation of small anterior portions of the limbal palisades hasan effect on the post-surgical success of corneal transplants and thispossibility bears further investigation.

Development of this technique as a way to visualize the palisadesrapidly, in-vivo, and without direct eye contact will provide cliniciansa valuable tool for monitoring patients with LSCD and for assessingsurvival of limbal stem cell transplants. Evaluation of the entirecorneal stem cell niche will allow targeted biopsies which shouldrequire less tissue and help to ensure the safety of the donor eye.Furthermore, this technique may allow early diagnosis of declining stemcell populations and allow early intervention. Conjunctivalization iscurrently the most reliable indicator of LSCD because other conditionsmay cause vascularization and inflammation, but earlier diagnosis ofLSCD with OCT may allow intervention to prevent the advancement of thedisease.

Visualization of palisades can assist diagnosis of LSCD, and enablespecific biopsy. In future explorations of stem cell niches OCT mayprove useful in identifying location in-vivo. Immunofluorescenceexperiments with limbal tissue to correlate the known structures visiblewith confocal microscopy and the newly described palisade structure andplanned experiments will include acquisition and analysis of imagesacquired with both OCT and confocal microscopy on the same eye.

In summary, the innovation disclosed herein, specifically, OCT, is ableto safely, rapidly and effectively image the palisades of Vogt withoutdirect contact to the eye. Thus, the innovation has the potential toenhance an understanding of this stem cell niche, allow development ofnew clinical and research techniques and assist in developing a betterunderstanding of the scope and function of corneal epithelial stem cellniche. Further, OCT has the potential to characterize the architectureof the palisades in vivo, more accurately harvest stem cells fortransplantation, track palisade structures for better diagnosis,follow-up and staging of treatment, and to assess and intervene in theprogression of stem cell depletion by monitoring changes in thestructure of the palisades.

What has been described above includes examples of the innovation. Itis, of course, not possible to describe every conceivable combination ofcomponents or methodologies for purposes of describing the subjectinnovation, but one of ordinary skill in the art may recognize that manyfurther combinations and permutations of the innovation are possible.Accordingly, the innovation is intended to embrace all such alterations,modifications and variations that fall within the spirit and scope ofthe appended claims. Furthermore, to the extent that the term “includes”is used in either the detailed description or the claims, such term isintended to be inclusive in a manner similar to the term “comprising” as“comprising” is interpreted when employed as a transitional word in aclaim.

What is claimed is:
 1. A method of visualizing the palisades of Vogtcomprising: imaging the palisades of Vogt via a non-contact in-vivo orex-vivo process; and monitoring the palisades of Vogt image on a displayscreen or by projecting the image in real time to monitor the palisadesof Vogt image during medical procedures.
 2. The method of claim 1,wherein imaging the palisades of Vogt via a non-contact in-vivo orex-vivo process comprises Optical Coherence Tomography.
 3. The method ofclaim 1, wherein imaging the palisades of Vogt via a non-contact in-vivoprocess comprises: imaging internal structures in biological tissuesin-vivo or ex-vivo by measuring a delay caused by reflection of lightfrom the image; and acquiring high-resolution images rapidly at apredetermined distance from the patient by using long-wavelength laserlight, wherein recognition of tissue boundaries depends on contrastbetween backscattered and/or reflected signal strength.
 4. The method ofclaim 3, wherein acquiring the high-resolution images are scanned atspeeds up to 400,000 axial scans per second.
 5. The method of claim 4,wherein the images are acquired using an Optical Coherence Tomographysystem.
 6. The method of claim 5, wherein the images acquired arereconstructed using C-mode slicing and/or 3D modeling.
 7. A method ofimaging palisades of Vogt comprising: imaging the palisades of Vogt viaa non-contact in-vivo or ex-vivo process; transferring the image to ananalyzing component; identifying the structures represented in the imageto evaluate their status; classifying the image in a category based onthe evaluation of the image; and storing the image in the category in adata storage component for future evaluation or comparison.
 8. Themethod of claim 7, wherein imaging the palisades of Vogt via anon-contact in-vivo or ex-vivo process comprises Optical CoherenceTomography.
 9. The method of claim 8, wherein prior to storing the imagein the category in a data storage component for future evaluation, themethod comprising monitoring the image to determine a trend representedby the data within the image.
 10. The method of claim 9, whereinmonitoring the image to determine a trend represented by the data withinthe image comprises taking a plurality of images over a period of timeand comparing a new image with the plurality of images stored in thedata storage component to determine the prognosis and/or progress of apatient.
 11. The method of claim 8, wherein identifying the structuresrepresented in the image to evaluate their status comprises determiningif a patient is healthy or unhealthy or to determine if tissue issuitable for donation or to determine if a patient is healthy enough tosustain a transplant.
 12. The method of claim 8, wherein classifying theimage in a category based on the evaluation of the image comprisescomparing a new image with stored images in the data storage componentto automatically classifying the image into the category.
 13. The methodof claim 8, wherein classifying the image in a category based on thedata in the image comprises manually identifying normal and abnormalcharacteristics and classifying the image in a specialized category forfurther evaluation.
 14. A system for imaging palisades of Vogtcomprising: an imaging component to take non-contact images of thepalisades of Vogt; an analysis component to analyze the images; and adata storage component to store the images in categories for furtherevaluation, wherein the images are reconstructed in C-mode slicing fromthe volume of images or in a 3D model via volume rendering.
 15. Thesystem of claim 14, wherein the imaging component comprises OpticalCoherence Tomography.
 16. The system of claim 15, wherein imaging thepalisades of Vogt is an in-vivo or ex-vivo process.
 17. The system ofclaim 16, wherein the analysis component includes: an identificationcomponent to determine if the image is from a healthy or an unhealthypatient; a classification component to classify the images in one of aplurality of categories based on the identification determination of theimages; and a monitoring component to monitor the health of the patientby comparing a new image with the images stored in the data storagecomponent.
 18. The system of claim 17, wherein the monitoring componentfurther displays the palisades of Vogt image on a display screen or as aprojection in real time to monitor the palisades of Vogt image duringmedical procedures.
 19. The system of claim 17, wherein theclassification component further automatically classifies the images inone of the pluralities of categories by comparing a new image withstored images in the data storage component.
 20. The system of claim 17,wherein the classification component further manually identifies normaland abnormal characteristics abnormalities and classifies the images ina specialized category for further evaluation.